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Mathematical modelling supports the existence of a threshold hydrogen concentration and media-dependent yields in the growth of a reductive acetogen.
Bioprocess and Biosystems Engineering ( IF 3.5 ) Pub Date : 2020-01-25 , DOI: 10.1007/s00449-020-02285-w
Nick W Smith 1, 2, 3, 4 , Paul R Shorten 2, 3 , Eric Altermann 2, 4 , Nicole C Roy 2, 4, 5 , Warren C McNabb 2, 5
Affiliation  

The bacterial production of acetate via reductive acetogenesis along the Wood-Ljungdahl metabolic pathway is an important source of this molecule in several environments, ranging from industrial bioreactors to the human gastrointestinal tract. Here, we contributed to the study of reductive acetogens by considering mathematical modelling techniques for the prediction of bacterial growth and acetate production. We found that the incorporation of a hydrogen uptake concentration threshold into the models improves their predictions and we calculated this threshold as 86.2 mM (95% confidence interval 6.1-132.6 mM). Monod kinetics and first-order kinetics models, with the inclusion of two candidate threshold terms or reversible Michaelis-Menten kinetics, were compared to experimental data and the optimal formulation for predicting both growth and metabolism was found. The models were then used to compare the efficacy of two growth media for acetogens. We found that the recently described general acetogen medium was superior to the DSMZ medium in terms of unbiased estimation of acetogen growth and investigated the contribution of yeast extract concentration to acetate production and bacterial growth in culture. The models and their predictions will be useful to those studying both industrially and environmentally relevant reductive acetogenesis and allow for straightforward adaptation to similar cases with different organisms.

中文翻译:

数学模型支持还原性乙酸原的生长中存在阈值氢浓度和取决于介质的产率。

沿伍德-隆达尔代谢途径通过还原性产乙酸作用产生的乙酸盐细菌,是从工业生物反应器到人胃肠道等多种环境中该分子的重要来源。在这里,我们通过考虑数学建模技术来预测细菌的生长和乙酸盐的产生,为还原性产乙酸素的研究做出了贡献。我们发现将氢吸收浓度阈值并入模型可以改善其预测,并且我们将该阈值计算为86.2 mM(95%置信区间6.1-132.6 mM)。Monod动力学和一阶动力学模型,其中包括两个候选阈值项或可逆Michaelis-Menten动力学,将其与实验数据进行比较,找到预测生长和代谢的最佳配方。然后将模型用于比较两种生长培养基对乙酸原的功效。我们发现,最近描述的通用产乙酸素培养基在无偏性估计产乙酸素方面优于DSMZ培养基,并研究了酵母提取物浓度对培养物中乙酸盐产生和细菌生长的贡献。该模型及其预测对研究工业和环境相关的还原性产乙酸的研究者将是有用的,并且可以直接适应具有不同生物的相似病例。我们发现,最近描述的通用产乙酸素培养基在无偏性估计产乙酸素方面优于DSMZ培养基,并研究了酵母提取物浓度对培养物中乙酸盐产生和细菌生长的贡献。该模型及其预测对研究工业和环境相关的还原性产乙酸的研究者将是有用的,并且可以直接适应具有不同生物的相似病例。我们发现,最近描述的通用产乙酸菌培养基在无偏性估计产乙酸菌方面优于DSMZ培养基,并研究了酵母提取物浓度对培养物中乙酸盐产生和细菌生长的贡献。该模型及其预测对研究工业和环境相关的还原性产乙酸的研究者将是有用的,并且可以直接适应具有不同生物的相似病例。
更新日期:2020-04-20
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